title: Real-time segmentation and tracking of brain metabolic state in ICU EEG recordings of burst suppression.
abstract: We provide a method for estimating brain metabolic state based on a reduced-order model of EEG burst suppression. The model, derived from previously suggested biophysical mechanisms of burst suppression, describes important electrophysiological features and provides a direct link to cerebral metabolic rate. We design and fit the estimation method from EEG recordings of burst suppression from a neurological intensive care unit and test it on real and synthetic data.
authors.forename: M Brandon
authors.initials: MB
authors.lastname: Westover
authors.forename: ShiNung
authors.initials: S
authors.lastname: Ching
authors.forename: Mouhsin M
authors.initials: MM
authors.lastname: Shafi
authors.forename: Sydney S
authors.initials: SS
authors.lastname: Cash
authors.forename: Emery N
authors.initials: EN
authors.lastname: Brown
mesh_terms: D000255:Adenosine Triphosphate / Q000378:metabolism; D000465:Algorithms; D001921:Brain / Q000378:metabolism*; D004569:Electroencephalography; D055724:Electrophysiological Phenomena; D006801:Humans; D007362:Intensive Care Units; D008959:Models, Neurological; D010100:Oxygen / Q000378:metabolism
chemical_list: D000255:Adenosine Triphosphate; D010100:Oxygen